the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Using geostationary-satellite-derived sub-daily fire radiative power variability versus prescribed diurnal cycles to assess the impact of African fires on tropospheric ozone
Haolin Wang
William Maslanka
Martin J. Wooster
Haofan Wang
Liang Feng
Shaojia Fan
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We develop a novel, dual-CTM bias correction framework to attribute summertime PM2.5 and ozone changes over eastern China during 2015–2024. The framework substantially reduces the CTM biases and reconciles the inter-model discrepancies in the attribution. Emission reductions dominate both the PM2.5 decline and ozone increase, but there is a marked transition of their role after 2019. Persistent unfavorable meteorological conditions contribute to ozone increase especially before 2019.
We develop a novel, dual-CTM bias correction framework to attribute summertime PM2.5 and ozone changes over eastern China during 2015–2024. The framework substantially reduces the CTM biases and reconciles the inter-model discrepancies in the attribution. Emission reductions dominate both the PM2.5 decline and ozone increase, but there is a marked transition of their role after 2019. Persistent unfavorable meteorological conditions contribute to ozone increase especially before 2019.
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
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We examine the impact of diurnally varying African biomass burning (BB) emissions on tropospheric ozone using GEOS-Chem simulations with a high-resolution satellite-derived emission inventory. Compared to coarser temporal resolutions, incorporating diurnal variations leads to significant changes in surface ozone and atmospheric oxidation capacity. Our findings highlight the importance of accurately representing BB emission timing in chemical transport models to improve ozone predictions.
We examine the impact of diurnally varying African biomass burning (BB) emissions on...